An important feature of a Long Term Evolution-Advanced (LTE-A) system of the 3rd Generation Partnership Project (3GPP) lies in that MIMO detection is adopted as a key technology of realizing high spectral efficiency to improve system capacity. Because of the requirement of the International Telecommunication Unit International Mobile Telecommunication-Advanced (ITU IMT-Advanced) for high spectral efficiency, the LTE-A puts forward that the spectral efficiency needs to meet the requirement for downlink with 30 bps/Hz and uplink with 15 bps/Hz. To satisfy these requirements, the LTE-A adopts 8 layers of downlink MIMO at most and 4 layers of uplink MIMO at most. So, supporting a multilayer MIMO detection technology becomes one of key technologies of deciding the performance of an LTE-A receiver.
In the MIMO detection technology, SD detection can make its performance approximate to the optimal performance, namely the Maximum Likelihood (ML) performance, and has a complexity much lower than that of the ML, so it is often selected to perform the MIMO detection. The SD detection is a process of cyclic search. Each cycle includes two steps: a first step of determining a smaller search radius of sphere space, namely searching a node with a distance to a received signal is less than a search radius; and the second step of replacing the previous search radius with the smaller search radius, so as to further reduce a search area. The two steps are repeated to gradually reduce the search area, until a maximum likelihood solution is found.
In Fixed-complexity Sphere Decoding (FSD) detection, in each layer of MIMO detection, a fixed number of nodes with a minimum distance to the received signal to determine the search radius, it has a fixed complexity and adopts a feedforward structure with a hardware-friendly feature, and it is implemented easily by Very Large Scale Integration (VLSI), so the FSD detection is often selected as an MIMO detection method of a terminal side.
A soft-output MIMO detection technology used in concert with a subsequent soft decoder can make a system to achieve a better performance. As shown in FIG. 1, the main flow of SD detection in the LTE-A system includes a QR decomposition (a matrix is decomposed into a normal orthogonal matrix and an upper triangular matrix), an equalizing signal calculation, ML path detection, ML complementary set path detection, and a calculation and output of soft value information. The soft value information is a Log Likelihood Ratio (LLR). The sphere search (including the ML path detection and the ML complementary set path detection) is the body of the MIMO detection, and the main calculation complexity depends on the complexity of the sphere search. How to make the performance of the soft-output multilayer MIMO detection approximate to the ML performance and decrease the calculation complexity of the sphere search as much as possible is the technical problem to be solved.